code: def test_do_validate(env_boston):
      exp = CVExperiment(
          model_initializer=Ridge,
          model_init_params={},
          feature_engineer=FeatureEngineer(
              [standard_scale], do_validate=True
          ),
      )
  
      for step in exp.feature_engineer.steps:
          assert step.original_hashes != {}
          assert step.updated_hashes != {}
          assert step.original_hashes != step.updated_hashes
  
file_path: hyperparameter_hunter/tests/integration_tests/feature_engineering/test_support.py
imports: from hyperparameter_hunter import Environment, CVExperiment, FeatureEngineer, EngineerStep
  from hyperparameter_hunter import Categorical, GBRT
  from hyperparameter_hunter.utils.learning_utils import get_boston_data
  import pytest
  from sklearn.linear_model import Ridge
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import QuantileTransformer, StandardScaler
label_desc: Use image node_id 5 for calling a global function with example usage: test_do_validate(env_boston) without return types